From gorgeous to grumpy

adjectives, age, and gender

Authors

  • Rosamund Moon University of Birmingham

DOI:

https://doi.org/10.1558/genl.v8i1.5

Keywords:

adjectives, ageing, cryptotypes, discourse, gender

Abstract

This paper presents a study of English adjectives used to describe men and women of different ages, and the gender- and age-based stereotypes revealed. Drawing on evidence in the 450-million-word Bank of English corpus, it examines central items such as young and old in combination with the gendered pairing man/men and woman/women, identifying sets of adjectival collocates associated with different age groups. These adjectives can be considered secondary age-markers, coding age through reference to physical and behavioural characteristics typical of different age groups and genders, and comprising a cryptotype (Whorf 1956) or covert category. This is discussed in the final part of the paper, along with deviant usage (‘young’ adjectives applied to older people, and vice versa). Since adjectives clustering with young mainly evaluate positively, those with old are mostly negative, there are implications for studies of ageism and sexism in language, and representation, age and gender more broadly.

Author Biography

Rosamund Moon, University of Birmingham

Rosamund Moon is a Senior Lecturer in the Department of English at the University of Birmingham. Her main research areas are lexis and phraseology, figurative language, lexicography, and corpus linguistics, and she has published widely on these areas: her publications include Fixed Expressions and Idioms in English: a Corpus-based Approach (1998: Oxford University Press); (with Murray Knowles) Introducing Metaphor (2006). She is currently researching discourses of ageing from a gender perspective, part of joint research with Carmen Rosa Caldas-Coulthard and Clare Anderson.

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Published

2014-03-17

How to Cite

Moon, R. (2014). From gorgeous to grumpy: adjectives, age, and gender. Gender and Language, 8(1), 5–41. https://doi.org/10.1558/genl.v8i1.5

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